Enhanced secure path selection model for underwater acoustic sensor networks using advanced machine learning and optimization techniques

Interest in underwater acoustic sensor networks (UW‐ASNs) has rapidly increased with the desire to control the large portion of the world covered by oceans. Energy efficiency is one of the major concerns in UW‐ASNs due to the limited energy budget of the underwater sensor nodes. In this paper, we tackle the problem of energy holes in UW‐ASNs while taking into consideration the unique characteristics of the underwater channel. We prove that we can evenly distribute the transmission load among sensor nodes provided that sensors adjust their communication range when they send or forward the periodically generated data. In particular, we propose a balanced routing strategy along with the associated deployment pattern that meticulously determines the load weight for each possible next hop that leads to fair energy consumption among all underwater sensors. Consequently, the energy holes problem is overcome, and hence, the network lifetime is improved. To the best of our knowledge, this is the first work that addresses the energy hole problem in UW‐ASNs. Copyright © 2016 John Wiley & Sons, Ltd.

Attack Simulation Model and Channel Statistics in Underwater Acoustic Sensor Networks

The Underwater Acoustic Sensor Network (UASN) is a large network in which the vicinity of a transmitting node is made up of numerous operational sensor nodes. The communication process may be substantially disrupted due to the underwater acoustic channel’s time-varying and space-varying features. As a result, the underwater acoustic communication system faces the problems of reducing interference and enhancing communication effectiveness and quality through adaptive modulation. To overcome this issue, this paper intends to propose a model for optimal path selection and secured data transmission in UASN via Long Short-Term Memory (LSTM) based energy prediction. The proposed model of transmitting the secured data in UASN through the optimal path involves two major phases. Initially, the nodes are selected under the consideration of constraints like energy, distance and link quality in terms of throughput. Moreover, the energy is predicted with the aid of LSTM and the optimal path is selected with the proposed hybrid optimization algorithm termed as Pelican Updated Chimp Optimization Algorithm (PUCOA), which is the combination of two algorithms including the Pelican Optimization Algorithm (POA) and Chimp Optimization Algorithm (COA). Further, the data is transmitted via the optimal path securely by encrypting the data with the proposed improved blowfish algorithm (IBFA). At last, the developed LSTM+PUCOA model is validated with standard benchmark models and it proves that the performance of the proposed LSTM+PUCOA model attains 90.85% of accuracy, 92.78% of precision, 91.78% of specificity, 89.79% of sensitivity, 7.21% of FPR, 89.76% of F1 score, 89.77% of MCC, 10.20% of FNR, 92.45% of NPV, and 10.22% of FDR for Learning percentage 70.

Routing plays a critical role in data transmission for underwater acoustic sensor networks (UWSNs) in the internet of underwater things (IoUT). Traditional routing methods suffer from high end-toend delay, limited bandwidth, and high energy consumption. With the development of artificial intelligence and machine learning algorithms, many researchers apply these new methods to improve the quality of routing. In this paper, we propose a Q-learning-based multi-hop cooperative routing protocol (QMCR) for UWSNs. Our protocol can automatically choose nodes with the maximum Q-value as forwarders based on distance information. Moreover, we combine cooperative communications with Q-learning algorithm to reduce network energy consumption and improve communication efficiency. Experimental results show that the running time of the QMCR is less than one-tenth of that of the artificial fish-swarm algorithm (AFSA), while the routing energy consumption is kept at the same level. Due to the extremely fast speed of the algorithm, the QMCR is a promising method of routing design for UWSNs, especially for the case that it suffers from the extreme dynamic underwater acoustic channels in the real ocean environment.

The properties of underwater acoustic channel are quite different from those of terrestrial wireless sensor networks, which brings many challenges to design an efficient media access control (MAC) protocol for underwater acoustic sensor networks (UWASNs). In order to overcome the long propagation delay and the funneling effect of UWASNs, a MAC protocol, named path-oriented code assignment (POCA) CDMA MAC (POCA-CDMA-MAC) protocol, is proposed in the paper. In the proposed protocol, a round-robin method and the CDMA technology are used to make the sink receive packets from multiple neighbors at the same time. Unlike other CDMA-based protocols using the transmitter-oriented code assignment (TOCA) or the receiver-oriented code assignment (ROCA), the POCA is used in the CDMA technology. Since the number of the path is much less than the number of nodes, the length of the spreading code used in systems with POCA is greatly shorter than those of the spreading code used in systems with TOCA or ROCA. Simulation results show that compared to existing MAC protocols for UWASNs, the proposed MAC protocol achieves a higher throughput, and a lower end-to-end delay.

Improving the energy efficiency of underwater acoustic sensor networks (UW-ASNs) is a crucial issue due to the reduced and nonrechargeable energy resource of the underwater sensor nodes. In this work, we address the energy sink hole problem in UW-ASNs while considering the unique and harsh characteristics of the underwater channel. Our goal is to determine the optimal deployment and routing settings that surmount the energy sink hole problem and hence maximize the network lifetime. We prove that sensors can evenly consume their initial battery power provided that first they adjust their transmission power when they transmit the route through traffic and second they are appropriately placed while deployed. Mainly, we propose a deployment scheme and the corresponding balanced routing strategy that lead to uniform energy consumption among all underwater sensors subject to a predefined reliability level at the sink. Specifically, we look for the optimal deployment settings especially in terms of nodes’ separation distances that help achieving uniform energy consumption in the network while satisfying the application requirement especially in terms of desired information reliability. Jointly, at the routing layer, we assume that each sensor is provided with the possibility of dynamically adjusting its transmission power up to a given number of levels N. To this goal, we mainly deal with two main cases: fixed and variable nodes separation distance. For the fixed case, we suppose that any two successive nodes in the network are equally spaced, and we strive for deriving the optimal distance as well as the optimal number of transmission power levels along with optimal load weight corresponding to every possible transmission power level for every sensor node. For the variable case, we deal with two subcases: first, we suppose that the distance separating successive nodes follows an arithmetic progression, and second, we assume that the distance separating successive nodes is following a geometric sequence. Note that for both cases, namely, fixed and variable, we succeed to determine the optimal distances separating successive nodes and the optimal number N of transmission power levels along with the corresponding optimal load weight that overcome the energy holes problem, and hence the network lifespan is maximized while respecting the desired reliability level.

Marine environmental monitoring, marine resource development, and maritime rights and interests protection had put great demands on underwater acoustic sensor networks. At the same time, it was found that the configuration and optimization of the underwater acoustic sensor network had important influence on the network performance and service quality in the uncertain marine environment. According to the characteristics of dynamic evolution of network topology and combining with different practical application scenarios, this article studied and discussed the model description, configuration mechanism, and optimization strategy of underwater acoustic sensor network. First, the classical underwater acoustic sensor network models were divided and discussed from three aspects: dimension, sensor types, and dynamic and static states. The characteristics of the six models are compared and analyzed. Second, according to the characteristics of six different models, the configuration mechanism and optimization strategy are discussed and classified. The configuration mechanism of models was studied from the aspects about determinism, self-adaptation, and group intelligence. The optimization strategy of models was discussed from the aspects about coverage, connectivity, energy consumption, time delay, data quality, and so on, and the relations and differences between different methods were compared and analyzed. Finally, the five future researches direction were expected, in order to provide a clear idea for further research in this field.

The Underwater Acoustic Sensor Networks (UWASN) consists of sensors that are deployed underwater for gathering information for the unexplored parts of oceans or rivers. UWASN consists of variable number of floating and anchored sensors, sink and vehicles that are deployed over an area to be explored. The characteristics of UWASN are mainly node mobility for floating, capacity for data collection and recording and autonomous vehicles which are battery operable. The communication is possible among underwater devices through optical waves, radio waves, electromagnetic and acoustics. Out of these, acoustics communication is best suited as it can carry digital information through underwater channel and can travel to longer distances. The communication can be classified in two parts: Single and multi hoping. But in underwater we use multi-hop communication for sending data from end nodes to sink nodes. The various challenges to UWASN are limited bandwidth, multipath fading, limited battery, limited data capacity and delay in propagation. Hence, in this paper we have focussed on various issues and challenges in underwater wireless sensor networks for acoustic communications.

Constrained by the interior properties of underwater acoustic channels such as limited bandwidth, time-varying multipath propagation, and large propagation delay, the design of MAC protocols for underwater acoustic sensor networks (UWSNs) poses significant challenges. Existing MAC protocols for UWSNs exhibit very low performance in channel utilization, throughput and end-to-end delay, as well as energy consumption since 1) they are based on the conventional stop-and-wait (SW) transmission scheme, and 2) fewer has error-control mechanism at data link layer. In this paper, we assume that the UWSN has a multi-hop topology, where there exist a sink node and some common sensor nodes; all the nodes adopt Time Division Multiple Access (TDMA) to access channel. First, we classify all the nodes into different groups according to the numbers of hops between these nodes themselves and the sink node; the nodes belonging to different groups adopt TDMA frames with different starting time. We then propose a new MAC protocol by incorporating the multi-channel technique and the juggling-like stop-and-wait (JSW) transmission scheme, which is called the JM-MAC. Finally, simulation results are presented to highlight its good performance in terms of channel utilization, throughput and delay.

A recommendation management defense mechanism based on trust model in underwater acoustic sensor networks

Underwater acoustic sensor networks are widely used for underwater information collection, environmental monitoring and assisted navigation. For energy limited underwater sensor nodes, the design of energy efficient protocols is a key problem in underwater acoustic sensor networks. In this paper, we propose two novel cluster formulation protocols for the Low Energy Adaptive Clustering Hierarchy Protocol (LEACH) in order to achieve further energy savings. The proposed cluster formulation protocols can significantly reduce the transmission collision probability during the cluster formulation process for underwater environments. Simulation results indicate that the proposed protocols outperform the standard LEACH protocol in terms of the network lifetime and the number of alive nodes. The proposed cluster formulation protocols can also be used with other modified LEACH protocols.

Ocean covers nearly 71% of our planet's surface, yet 95% of the ocean remains unexplored by human being, and wireless sensor networks are envisioned to perform monitoring tasks over the large portion of our world. However, deploying wireless sensor networks on the sea poses many challenges and for maritime surveillance security applications we may need to deploy sensors both on the sea surface and underwater for three-dimensional detection. In this paper, we propose a hybrid ocean sensor networks called Double-head maritime Sensor Networks (DSNs), which combine the advantages of wireless sensor networks and underwater acoustic sensor networks. By leveraging the unique characteristics of DSNs, we design a localization scheme LDSN which is consisted of two algorithms SML and FLA. We first use SML to localize moored anchor nodes as seed nodes. After the underwater sensor networks have been localized, the floating double-head nodes can figure out its instant position via FLA algorithm. We evaluate the scheme by simulations and the results show that the scheme can achieve a high localization accuracy.

We propose a localization scheme for underwater acoustic sensor networks (UWSN) that does not require a priori infra-structure or synchronization between nodes. An autonomous underwater vehicle (AUV) aids in localizing the sensor nodes while roaming across the underwater sensor field. The objectives of this paper are to describe how to localize nodes using AUV and to describe the tradeoffs involved, i.e. ratio of localized nodes and localization accuracy. We show that localization success improves as the duration of the AUV localization process increases. In addition, we investigated localization using two methods, bounding-box and triangulation. The former achieves a higher localization ratio but with a higher error. In certain scenarios, we achieved 100% nodes localized with 3% error.

Underwater wireless sensor networks nodes deployment optimization problem is studied and underwater wireless sensor nodes deployment determines its capability and lifetime. If no underwater wireless sensor node is available in the monitoring area of underwater wireless sensor networks due to used up energy or any other reasons, the monitoring area where is not detected by any underwater wireless sensor node forms coverage holes. In order to improve the coverage of the underwater wireless sensor networks and prolong the lifetime of the underwater wireless sensor networks, based on the perception model, establish nodes detection model, combining with the data fusion. Because the underwater wireless sensor networks nodes coverage holes appear when the initial randomly deployment, a nodes deployment algorithm based on perception model of underwater wireless sensor networks is designed in this article. The simulation results show that this algorithm can effectively reduce the number of deployment underwater wireless sensor networks nodes, improve the efficiency of underwater wireless sensor networks coverage, reduce the underwater wireless sensor networks nodes energy consumption, prolong the lifetime of the underwater wireless sensor networks.

UASN (Underwater Acoustic Sensor Network) has intrinsic impediments, since it is utilized and utilizes acoustic signs to impart in the sea-going world. Examples include long delays in propagation, limited bandwidth, high transmitting energy costs, very high attenuation in the signal, expensive implementation and battery replacement etc. The UASN routing schemes must therefore take account of these features to achieve balance energy, prevent void hole and boost network life. One of the significant issue in routing is the presence of void node. A void node is a node that does not have any forwarder node. The presence of void may cause the bundle conveyance in the steering time which prompts information misfortune. The gap during steering influences the network execution regarding proliferation delay, vitality utilization and network lifetime, and so forth. So with the objective to remove the void node in the networks, this work presents an energy efficient optimal path routing for void avoidance in underwater acoustic sensor networks. This work uses the concept of gray wolf optimization algorithm to calculate the fitness function and that fitness function is used to select the best forwarder node in the networks. This work only consider the vertical directions which further reduces the end to end delay. The proposed work has been simulated on MATLAB and performances are evaluated in terms of broadcast copies of data, energy tax, and packet delivery ratio, number of dead nodes, network lifetime and delay.